AI AND TRANSFORMATION OF SPA MANAGEMENT: KEY ETHICAL CONSIDERATIONS
Abstract
This paper reviews available scientific literature on how artificial intelligence (AI) is transforming spa management and highlights core ethical considerations for responsible adoption. AI enables personalized wellness recommendations, demand forecasting, dynamic pricing, energy optimization, predictive maintenance, and automation of scheduling and customer service, potentially improving service quality and operational efficiency. These benefits raise ethical AI issues including fairness in personalization and pricing, explainability of recommendations, bias in customer profiling, and accountability for harm when automated decisions affect access to services. Data privacy is critical because spa settings involve sensitive health, biometric, and behavioral data; key requirements include data minimization, purpose limitation, secure storage, informed consent, and careful governance of third-party vendors and cross-border data flows. Integration challenges include interoperability with legacy booking and facility systems, cybersecurity risks, staff training, and managing model drift over time. Findings of the review are consolidated into the SPA-ETHICS Governance Framework, which operationalizes eight ethical pillars (transparency, accuracy, data privacy, accountability, non-deception, fairness, human oversight, and responsibility) across the spa AI lifecycle by linking use cases to controls, decision rights, escalation pathways, and audit mechanisms. The review highlights the need for human oversight and continuous monitoring to preserve integrity, trust, and safety in AI-enabled spa operations.
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Balasubramaniam, N., Kauppinen, M., Rannisto, A., Hiekkanen, K., & Kujala, S. (2023). Transparency and explainability of AI systems: From ethical guidelines to requirements. Information and Software Technology, 159(1), 107197. https://doi.org/10.1016/j.infsof.2023.107197
Bhuiyan, M. S. (2024). The role of AI-enhanced personalization in customer experiences. Journal of Computer Science and Technology Studies, 6(1), 162–169. https://doi.org/10.32996/jcsts.2024.6.1.17
Buhalis, D., & Moldavska, I. (2022). Voice assistants in hospitality: using artificial intelligence for customer service. Journal of Hospitality and Tourism Technology, 13(3), 386–403. https://doi.org/10.1108/JHTT-03-2021-0104
Cheong, B. C. (2024). Transparency and accountability in AI systems: safeguarding wellbeing in the age of algorithmic decision-making. Frontiers in Human Dynamics, 6(1), 1421273. https://doi.org/10.3389/
fhumd.2024.1421273
Frenette, J. (2023). Ensuring human oversight in high-performance AI systems: A framework for control and accountability. World Journal of Advanced Research and Reviews, 20(2), 1507–1516. https://doi.org/
10.30574/wjarr.2023.20.2.2194
Gkintoni, E., Telonis, G., Tsimakis, A., Halkiopoulos, C., & Boutsinas, B. (2024). Integrating AI-powered personalization via neurobiologically informed DBT in smart wellness resorts. In International conference of the international association of cultural and digital tourism (pp. 923–953). Springer Nature. https://doi.org/10.1007/978-3-031-78471-2_40
Henriques, H., & Pereira, L. N. (2024). Hotel demand forecasting models and methods using artificial intelligence: A systematic literature review. Tourism & Management Studies, 20(3), 39–51. https://doi.org/
10.18089/tms.20240304
Johnson, J. (2025). The Impact of AI-Powered Technologies on Customer Satisfaction and Operational Efficiency in the Hospitality Industry [Doctoral dissertation, National College of Ireland].
Koranteng, A., Adongo, C. A., Osei, C. A., & Dayour, F. (2025). What happens at Trinity Spa stays at Trinity Spa: spa-goers’ privacy expectations. International Journal of Spa and Wellness, 8(3), 576–598. https://doi.org/10.1080/24721735.2025.2543690
Lambrecht, F., & Moreno, M. (2024). What is AI ethics?. American Philosophical Quarterly, 61(4), 387–401. https://doi.org/10.5406/
21521123.61.4.07
Ljepava, N. (2022). AI-enabled marketing solutions in marketing decision making: AI application in different stages of marketing process. Tem Journal, 11(3), 1308–1315. https://doi.org/10.18421/TEM113-40
Marcus, A. (2025). Artificial intelligence in hospitality service delivery. Journal of Hospitality, 7(1), 13–31.
Martin, K. D., & Zimmermann, J. (2024). Artificial intelligence and its implications for data privacy. Current Opinion in Psychology, 58(1), 101829. https://doi.org/10.1016/j.copsyc.2024.101829
Mittelstadt, B. (2019). Principles alone cannot guarantee ethical AI. Nature machine intelligence, 1(11), 501–507. https://doi.org/10.1038/
s42256-019-0114-4
Niederwolfsgruber, F. (2026). AI Process Automation in Customer Service in the Tourism Industry [Doctoral dissertation, Libera Universitá di Bolzano].
Okonkwo, R., Folorunso, A., Ogundipe, F., & Tettey, C. Y. (2025). Explainable Artificial Intelligence (Al) through human-AI collaborative frameworks: Quantifying trust and interpretability in high-stakes decisions. Comput. Sci. IT Res. j, 6(5), 333–354. https://doi.org/
10.51594/csitrj.v6i5.1934
Osei-Mensah, B., Asiamah, E. O., & Sackey, R. (2023). Strategic communication and artificial intelligence: Reviewing emerging innovations and future directions. Archives of Business Research, 11(1), 85–102. https://doi.org/10.14738/abr.111.13616
Purohit, P., Al Nuaimi, F., & Nakkolakkal, S. (2024, May). Data Governance, Privacy, Data Sharing Challenges. In SPE Gas & Oil Technology Showcase and Conference (p. D021S031R001). SPE. https://doi.org/10.2118/219172-MS
Sarkadi, S., Mei, P., & Awad, E. (2023, May). Should my agent lie for me? public moral perspectives on deceptive AI. In International Conference on Autonomous Agents and Multiagent Systems (pp. 151–179). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-56255-6_9
Shaik, M. (2023). Predictive maintenance in hospitality using ai and aws bedrock. IJLRP-International Journal of Leading Research Publication, 4(2), 1–10.
Thorne, S. (2024). Understanding the interplay between trust, reliability, and human factors in the age of generative AI. International Journal of Simulation--Systems, Science & Technology, 25(1). https://doi.org/10.5013/IJSSST.a.25.01.10
UNESCO. (2022). Recommendation on the ethics of artificial intelligence. Retrieved April 2, 2026, from: https://www.unesco.org/en/
articles/recommendation-ethics-artificial-intelligence
Verčič, D., Selaković, M., Hung-Baesecke, F., Cheng, Y., Verčič, A. T., Ljepava, N., & Stavreva, S. (2025). Ethical Standards and Guidelines For the Use of Artificial Intelligence in Public Relations. IPRA.
Żywiołek, J. (2024). Empirical examination of ai-powered decision support systems: ensuring trust and transparency in information and knowledge security. Zeszyty Naukowe. Organizacja i Zarządzanie/Politechnika Śląska, 197(1), 679–695. https://doi.org/10.29119/1641-3466.2024.197.37
